About: Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-Cov-2 infection: a multicenter cohort study (PREDI-CO study)

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About: Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-Cov-2 infection: a multicenter cohort study (PREDI-CO study) Goto Sponge NotDistinct Permalink

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-Cov-2 infection: a multicenter cohort study (PREDI-CO study)
Creator	Gaibani, Paolo Puoti, Massimo Attard, Luciano Bartoletti, Michele Badia, Lorenzo Barchiesi, Francesco Bussini, Linda Campoli, Caterina Codeluppi, Mauro Cristini, Francesco Fornaro, Giacomo Giannella, Maddalena Licci, Alberto Menozzi, Marianna Merli, Marco Meschiari, Marianna Mussini, Cristina Pancaldi, Livia Pascale, Renato Pasquini, Zeno Ranieri, Vito Rapuano, Silvia Rinaldi, Matteo Saracino, Annalisa Scudeller, Luigia Tadolini, Marina Tedeschi, Sara Tonetti, Tommaso Trapani, Filippo Gm, Liuzzi Mc, Leoni Omo, Dell Onofrio, D Vm, Ranieri
Source	Elsevier; Medline; PMC
abstract	OBJECTIVES: We aimed to develop and validate a risk score to predict severe respiratory failure (SRF) among patients hospitalized with coronavirus disease-2019 (COVID-19). METHODS: We performed a multicentre cohort study among hospitalized (>24 hours) patients diagnosed with COVID-19 from February 22 to April 3 2020, at 11 Italian hospitals. Patients were divided into derivation and validation cohorts according to random sorting of hospitals. SRF was assessed from admission to hospital discharge and was defined as: SpO2<93% with 100% FiO2, respiratory rate (RR)>30bpm, or respiratory distress. Multivariable logistic regression models were built to identify predictors of SRF, β-coefficients were used to develop a risk score. Trial Registration NCT04316949. RESULTS: We analyzed 1113 patients (644 derivation, 469 validation cohort). Mean (±standard deviation)age was 65.7(±15) years, 704 (63.3%) were male. SRF occurred in 189/644 (29%) and 187/469 (40%) patients in derivation and validation cohort, respectively. At multivariate analysis, risk factors for SRF in the derivation cohort assessed at hospitalization were age ≥70 years [OR 2.74 (95%CI 1.66-4.50)], obesity [OR 4.62 (95%CI 2.78-7.70)], body temperature ≥38°C [OR 1.73 (95%CI 1.30-2.29)], RR ≥22bpm [OR 3.75 (95%CI 2.01-7.01)], lymphocytes ≤900/mm(3) [OR 2.69 (95%CI 1.60-4.51)], creatinine ≥1 mg/dl [OR 2.38 (95%CI 1.59-3.56)], C-reactive protein ≥10mg/dl [OR 5.91 (95%CI 4.88-7.17)], and lactate dehydrogenase ≥350IU/L[OR 2.39 (95%CI 1.11-5.11)]. Assigning points to each variable an individual risk score (PREDI-CO score) was obtained. Area under receiver-operator curve (AUROC) was 0.89 (0.86-0.92). At score of >3, sensitivity, specificity, positive and negative predictive values were 71.6%(65-79%), 89.1% (86-92%), 74%(67-80%), and 89%(85-91%), respectively;. PREDI-CO score showed similar prognostic ability in the validation cohort: AUROC 0.85 (0.81-0.88). At score of >3, sensitivity, specificity, positive and negative predictive values were 80% (73-85%), 76 (70-81%), 69%(60-74%) and 85% (80-89%), respectively. CONCLUSION: PREDI-CO score can be useful to allocate resources and prioritize treatments during COVID-19 pandemic.
has issue date	2020-08-08(xsd:dateTime)
bibo:doi	10.1016/j.cmi.2020.08.003
bibo:pmid	32781244
has license	no-cc
sha1sum (hex)	a029504e3d1be5a4db2d89558f56e94cf4cbce32
schema:url	https://doi.org/10.1016/j.cmi.2020.08.003
resource representing a document's title	Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-Cov-2 infection: a multicenter cohort study (PREDI-CO study)
has PubMed Central identifier	PMC7414420
has PubMed identifier	32781244
schema:publication	Clin Microbiol Infect
resource representing a document's body	covid:a029504e3d1be5a4db2d89558f56e94cf4cbce32#body_text
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